I can't see where you’re comin' from / but I know just what you’re runnin' from / And what matters ain't the who's baddest / but the ones who stop you fallin' from your ladder.

For a little over four years now I’ve had a summer time hobby of trying to predict plausible performance levels from various QBs for the upcoming football season. I have tried to root these projections as deeply into the bedrock of reality as is possible for a figment of one’s imagination and at this point there is a codex of sorts in the diary archives describing my methods. It’s fun to go back and see what worked and learn from what didn’t.There’s something there, man.

For Devin Gardner 2013 I laid out two stat lines hinging on two sets of assumptions—a reasonable/prudent set, and a ‘sexy’ set. The reasonable prediction: Gardner would complete 225 of 360 passes for 2900 yards, 23 TDs, and 10 INTs. In reality he went 208 of 345 for 2960 yards, 21 TDs, and 11 INTs. There’s a HEAVY dose a good fortune involved there but, hot damn, that’s pretty good. The assumptions here were basically looking at only QB stats and nothing else Devin had shown enough in his 5 QB starts during the 2012 season to perform at the “seasoned veteran QB” level which I think of as an incumbent with 2 years of experience in tow. That's a brutal benchmark, IMO but that's what I measure guys up against. That's what we want them to be.

Anyway, the sexy set of assumptions were:

Devin has elite talent. I believe this one held. More on that later.

The O-line would be fine despite the possibility of being “a touch weaker than last year (2012).” Eh boy…

The offensive scheme would be well tailored to Gardner’s skill set and that of the support around him. This was sometimes true but not consistently often enough for Borges to keep his job.

Ok, so the necessary assumptions for DG to be the second coming of Vince Young vanished into the ether. But those last two assumptions about the support and scheme are really kind of baked into the reasonable prediction too. For my money, the fact that DG put up the numbers he was able to in spite of the glaring flaws of the team is a testament to just how good he can be if the conditions are reasonable.

The fact that there are so many straight-faced questions being asked about Devin Gardner’s incumbency status is ludicrous. Sure, numbers don’t tell the whole story but they tell a good part of it. DG went from being one of the darlings of the 2013 Manning Passing Academy to needing to prove his talent simply because he couldn't compensate for all of the flaws around him last season. He did as well as could reasonably be expected without adjusting for other very real headwinds.

Yesterday I did some quick research on an improved red zone efficiency metric, which generated some discussion on other potential ways to look at a team's offensive productivity. One of the suggestions that immediately intrigued me was points per possession (thanks Gene). This metric is becoming more and more popular in basketball; I'm sure several of us have read a decent amount on this from Pomeroy, Gasaway (formerly Big Ten Wonk), etc., as Brian references their tempo-free stats on occasion. Dylan at UMHoops uses them as well, for those of you who follow (if you don't, you should).

Points per possession would seem like a pretty easy number to come up with. Well, total points scored is easy to find, but number of possessions... not so much (if anybody has a source for this data, I'd love it if you would share). To get there, I looked at all possible ways that a possession can come to an end (once again drawing on things learned from Pomeroy and Gasaway): Punt, Turnover (downs, int, fumble), Score (and thus a kickoff). So to determine total possessions, I used:

Punts + Turnovers + Kickoffs - Number of Games (each team has one kickoff per game that was not the result of a possession).

There are still some flaws with the above:

I currently have no way to account for a possession that ends at the end of a half.

A muffed and lost punt (or a Gordon/Vinopal special: pick -> lost fumble) will show up as a possession (turnover), but these probably shouldn't be taken into account when considering offensive efficiency.

Points scored without the offense's involvement (pick-six, punt/kick return etc) should not count towards offensive efficiency. I am not sure whether or not the NCAA's "Team Scoring Offense -- Total Points" adjusts for this or not.

I welcome any suggestions or further critique.

(And since this is MGoBlog) Well, that's a lot of words, how about a...

Chart

Rank

Team

Kickoffs

Games

Punts

Turnovers

Possessions

Points

Points Per Possession

1

Nevada

32

4

8

5

41

179

4.37

2

Stanford

36

4

7

5

44

192

4.36

3

Indiana

22

3

9

1

29

124

4.28

4

Ohio St.

36

4

14

3

49

197

4.02

5

TCU

30

4

13

6

45

178

3.96

6

Michigan

28

4

13

6

43

165

3.84

7

Oklahoma St.

30

3

12

6

45

171

3.80

8

Air Force

26

4

11

5

38

144

3.79

9

Kentucky

27

4

13

3

39

147

3.77

10

Alabama

28

4

11

7

42

158

3.76

11

Utah

30

4

15

7

48

177

3.69

12

Wisconsin

29

4

13

5

43

158

3.67

13

Oregon

41

4

18

9

64

231

3.61

14

Boise St.

24

3

7

6

34

121

3.56

15

Houston

32

4

12

10

50

177

3.54

16

Florida

27

4

11

9

43

151

3.51

17

Southern California

26

4

12

9

43

148

3.44

18

Florida St.

26

4

11

8

41

141

3.44

19

East Carolina

22

3

15

3

37

127

3.43

20

Iowa

25

4

17

6

44

144

3.27

21

Nebraska

28

4

16

11

51

160

3.14

22

California

27

4

14

9

46

144

3.13

23

Mississippi

26

4

13

12

47

144

3.06

24

UTEP

22

4

11

8

37

113

3.05

25

Auburn

23

4

16

8

43

131

3.05

26

Hawaii

29

4

12

11

48

146

3.04

27

Army

22

4

18

3

39

118

3.03

28

North Carolina St.

28

4

20

6

50

151

3.02

29

Clemson

21

3

17

4

39

117

3.00

30

Michigan St.

27

4

20

6

49

147

3.00

31

San Diego St.

30

4

18

7

51

153

3.00

32

South Carolina

24

4

13

8

41

123

3.00

33

Missouri

30

4

17

8

51

151

2.96

34

Tulsa

30

4

15

10

51

151

2.96

35

Miami (FL)

19

3

8

10

34

100

2.94

36

Idaho

23

4

13

11

43

126

2.93

37

Virginia

18

3

12

6

33

96

2.91

38

Fresno St.

20

3

15

5

37

107

2.89

39

Georgia Tech

23

4

11

13

43

124

2.88

40

Syracuse

24

4

18

7

45

129

2.87

41

Arizona

27

4

17

8

48

137

2.85

42

South Fla.

18

3

8

11

34

97

2.85

43

Virginia Tech

25

4

11

8

40

114

2.85

44

Texas A&M

23

3

13

11

44

123

2.80

45

Central Mich.

22

4

16

9

43

120

2.79

46

Arizona St.

28

4

15

13

52

145

2.79

47

Maryland

26

4

22

6

50

138

2.76

48

Arkansas

24

4

13

14

47

126

2.68

49

Kansas St.

24

4

20

6

46

123

2.67

50

Wake Forest

24

4

21

8

49

131

2.67

51

Northwestern

25

4

19

5

45

120

2.67

52

Oklahoma

27

4

23

5

51

136

2.67

53

Minnesota

22

4

13

10

41

106

2.59

54

Oregon St.

16

3

17

1

31

80

2.58

55

Connecticut

27

4

19

10

52

133

2.56

56

Texas Tech

18

3

14

11

40

101

2.53

57

Troy

28

4

19

11

54

136

2.52

58

Duke

21

4

18

14

49

123

2.51

59

Navy

14

3

11

4

26

64

2.46

60

Mississippi St.

17

4

16

10

39

94

2.41

61

Baylor

22

4

20

7

45

108

2.40

62

Georgia

20

4

19

7

42

97

2.31

63

Middle Tenn.

24

4

20

14

54

124

2.30

64

UAB

17

4

19

12

44

101

2.30

65

Arkansas St.

21

4

22

10

49

112

2.29

66

SMU

22

4

21

11

50

114

2.28

67

Penn St.

22

4

11

12

41

93

2.27

68

LSU

24

4

18

9

47

106

2.26

69

UCF

20

4

18

9

43

96

2.23

70

Kansas

17

4

18

9

40

89

2.23

71

Northern Ill.

19

4

17

8

40

89

2.23

72

Bowling Green

23

4

20

12

51

112

2.20

73

Illinois

15

3

15

8

35

76

2.17

74

Texas

23

4

16

13

48

104

2.17

75

West Virginia

20

4

20

12

48

100

2.08

76

Tennessee

22

4

26

10

54

112

2.07

77

Cincinnati

19

4

25

10

50

102

2.04

78

Southern Miss.

21

4

19

9

45

91

2.02

79

Fla. Atlantic

14

3

17

5

33

66

2.00

80

Iowa St.

19

4

16

10

41

81

1.98

81

Washington

16

3

21

6

40

79

1.98

82

Miami (OH)

20

4

15

12

43

84

1.95

83

Boston College

14

3

14

8

33

64

1.94

84

Utah St.

19

4

23

10

48

93

1.94

85

Western Mich.

16

3

16

16

45

87

1.93

86

Toledo

17

4

25

9

47

90

1.91

87

Louisville

14

3

15

9

35

67

1.91

88

North Carolina

14

3

11

12

34

65

1.91

89

Pittsburgh

14

3

15

8

34

65

1.91

90

Purdue

19

4

20

11

46

87

1.89

91

Temple

19

4

22

9

46

87

1.89

92

Notre Dame

21

4

21

11

49

92

1.88

93

Rutgers

15

3

14

8

34

63

1.85

94

UCLA

19

4

18

14

47

87

1.85

95

Colorado

12

3

17

8

34

62

1.82

96

Eastern Mich.

16

4

23

13

48

82

1.71

97

Tulane

15

3

17

8

37

63

1.70

98

Western Ky.

15

4

24

7

42

71

1.69

99

Marshall

16

4

25

11

48

80

1.67

100

UNLV

17

4

30

7

50

83

1.66

101

Akron

17

4

26

4

43

70

1.63

102

Ohio

17

4

21

14

48

76

1.58

103

Ball St.

16

4

20

9

41

63

1.54

104

Rice

19

4

23

11

49

75

1.53

105

La.-Monroe

9

3

17

9

32

48

1.50

106

Washington St.

17

4

26

14

53

77

1.45

107

Memphis

16

4

28

9

49

71

1.45

108

Vanderbilt

11

3

25

3

36

52

1.44

109

BYU

15

4

21

11

43

60

1.40

110

Kent St.

13

3

20

9

39

54

1.38

111

New Mexico St.

11

3

22

4

34

47

1.38

112

Louisiana Tech

18

4

23

15

52

71

1.37

113

Colorado St.

14

4

15

16

41

55

1.34

114

Wyoming

12

4

22

11

41

55

1.34

115

La.-Lafayette

11

3

24

7

39

52

1.33

116

FIU

13

3

24

13

47

62

1.32

117

North Texas

14

4

24

13

47

62

1.32

118

Buffalo

16

4

30

15

57

68

1.19

119

San Jose St.

12

4

29

8

45

36

0.80

120

New Mexico

11

4

32

19

58

41

0.71

Michigan is near the top of the list (6th); this is no surprise. Also near(er) the top and of interest to some folks around these parts is Stanford (2nd), along with this week's opponent, Indiana (3rd), and the Buckeyes (4th).

I would love it if this sort of statistic would eventually make its way into the "mainstream." Again, it seems like basketball is leading the charge for tempo-free stats, but there's no reason that we can't look at it for football as well. Perhaps we could lay this up against the dreaded time of possession stat and look for correlation -- or lack thereof. I also think it would be an interesting metric to use along with the work that The Mathlete has done -- we could start to replace some of the assumptions (Top 20 offense, average defense, etc) with data.

As I said above, please feel free to rip this apart and tell me that I'm a flaming idiot, or offer suggestions, critiques, ways to improve.

Pop quiz hotshot, who has the best offense in the Big Ten? If you don't know the answer or want to follow along with some simple stat manipulation, read and find out.

As usual, 12 data points is not enough to draw solid conclusions but if you didn't enjoy making statistical interpretations about college football you probably wouldn't be reading mgoblog.

Scoring Offense

As everyone knew, going into the OSU game Michigan had the best scoring offense in the Big Ten. Unfortunately that 10 spot we put up drops us all the way to 4th. How do we drop so quickly from 1st to 4th? What it really means is that we are in the 1st tier of offenses and a virtual tie for 2nd. If we had made that field goal (or gotten a safety) we would have been 2nd place in the Big Ten.

So how does the Big Ten stack up? Well, Wisconsin is the best scoring offense in the conference. Penn State, Michigan State, Michigan and Ohio State make up the rest of tier 1. Purdue*, Northwestern, Indiana and Iowa are the tier 2 offenses. Finally, Minnesota and Illinois bring up the rear.

Points per game

Standard Deviation

Wisconsin

31.09

11.1

Penn St

29.67

12.54

Michigan St

29.58

10.93

Michigan

29.50

15.6

Ohio St

29.25

8.8

Purdue

27.83

13.27

Northwestern

25.08

9.88

Indiana

23.50

8.28

Iowa

23.08

9.41

Minnesota

21.58

13.84

Illinois

20.2

14.25

The main point to take away is that our offense was comparable to the Big Ten's offenses this year. Would you have said that last year? The other important thing to note is the standard deviation. Michigan was the most inconsistent of all Big Ten teams. Shocking statistical analysis there. Isn't it a good thing we can look at the numbers to see things we could never have known by watching the games?

Cupcakes aren't a high fiber diet

Again as everyone knew, part of that number 1 ranking was built out of baby seal carcasses. Michigan wasn't the only team that played a cupcake though. How can we adjust for these blowout games?

Well, one possibility is to look at performance against average points allowed. However, this takes some work and is already covered in great detail by The Mathlete. I prefer a quick and dirty approach. We take out the high and low score for each team to get more of a sense of what the consistent performance of the offense is.

Adjusted PPG

Std Dev

Wisconsin

31.89

8.49

Penn St

29.70

8.92

Michigan St

29.30

8.56

Ohio St

29.10

6.67

Purdue

28.20

8.00

Michigan

28.10

11.33

Northwestern

24.1

6.97

Indiana

23.70

5.50

Iowa

22.50

7.01

Minnesota

21.7

11.66

Illinois

19.63

10.7

The only change in the adjusted points per game is that Michigan drops from 4th to 6th. It still remains in tier 1 though, along with Wisconsin, Penn State, Michigan State, Ohio State and this time Purdue. Northwestern falls more in line with the tier 2 offenses along with Indiana and Iowa. Minnesota and Illinois are still tier 3, although Illinois should probably be it's own tier 4. By the way, who wants to guess how many of the high scores that got eliminated were scored against Michigan?**

What does this all mean?

Everybody will have their own interpretation of these stats. When combined with the eyeball test, I think that it means our offense has made a lot of improvement over last year. It's not quite the offensive juggernaut we hope to see soon, but a lot of that could be explained by a true freshman QB and Molk's absence. We'll see how much more they improve next year, but I think there is a real reason for a lot of hope on the offensive side of the ball.

* Purdue is hard to judge because it is basically in between tier 1 and tier 2. There is a gap between the tier 1 teams and Purdue so I made them tier 2. I probably should have included the Boilermakers in tier 1 though, as we'll see in the next section.

** Trick question. Surprisingly, only Wisconsin scored their season-high against us. Although, Illinois and Indiana came within a touchdown of their season highs when they played us.

This is a follow-up to my number crunching from last night (found here) in which I tried to figure out an alternate way of looking at defensive red zone performance. The method normally used is just to look at what percentage of red zone trips result in points. The problem with this is that it treats field goals as having the same value as touchdowns - this is not true. I tried weighting the values of field goals relative to touchdowns, but someone in the comments pointed out a simpler method to create the sort of metric I was looking for: Points per red zone trip (PPT). On this scale, a team that scores a TD on every red zone trip would show 7 PPT, a team that scored a field goal every time would get 3 PPT, etc. I'll go back later tonight to edit the defensive charts with this stat as well. Someone else in the comments asked what the offensive numbers looked like, so without further ado, here's the

Well, hell. What do you make of that? I can't see much of a pattern there at all. I guess maybe the teams that play more of a smashmouth style are higher up on the list? I'm willing to chalk this up to limited sample size and uneven competition, and just come back to this in a few weeks. It does make me question how much sample size and opponent quality affected the defensive numbers as well. What do you think?

I was reflecting on our win yesterday, and how crucial it was that our defense held IU to field goals on several drives that went deep into our territory. I got to thinking about red zone percentage numbers - the way everyone calculates them, a field goal is worth the same as a touchdown. Doesn't make much sense, does it? If the other team's going to score, you'd much rather have a team that allows three points per trip inside the 20 than one that allows six. So, I went to the NCAA website and grabbed the redzone defense numbers, and calculated a sort of weighted percentage. Basically it's this:

Yes, I know that a TD usually winds up being worth 7 points, but a 2:1 value for TDs vs. FGs seemed like a good starting point. Why did I bother doing this? Well, mostly just to see if numbers justified my perception that regardless of how the defense as a whole plays, it's really tightened up inside the 20s. How do we measure up? Well, I put the whole Big 10 on a...

Chart:

School

Drives

Red zone %

Rank

Weighted red zone %

Weighted rank

PPT

Penn State

8

63%

7

44%

3

2.88

Indiana

10

70%

20

55%

17

3.80

Michigan

15

73%

27

57%

21

3.87

Iowa

7

100%

111(t)

64%

42

4.14

Minnesota

12

83%

63

67%

51

4.50

Purdue

16

81%

58

75%

89

5.19

Illinois

10

90%

93

80%

106

5.50

Northwestern

15

87%

79

80 %

108

5.53

Wisconsin

13

92 %

102

81 %

110

5.46

Michigan State

12

100 %

111(t)

88 %

113

5.92

Ohio State

5

100 %

111(t)

90 %

118

6.40

Note - "Red zone %" and "Rank" are the defensive numbers straight from the NCAA website, and the weighted numbers are mine.

So what does this mean?

It's still early in the season, but we can start to see a few things.

First, I was right - Michigan is near the top of the conference, and has done a pretty good job of keeping folks out of the endzone when they get inside the 20.

Holy hell, MSU. If we get in the red zone, we should get points - probably 6 of them.

Iowa's interesting - every red zone trip, they've given up a score. However, they've done a damn god job of limiting people to field goals. (Admittedly, that's on only 7 drives.)

Penn State's been pretty darn good, allowing a TD on only 25% of their red zone trips.

Before you start gloating about OSU being at the bottom of the list, look at the number of drives. That's right, they're allowing an average of 1.25 red zone drives per game. Of course, they gave up touchdowns on almost every trip, but small sample size blah blah.

Other random things of interest:

Virginia Tech checks in at #4 nationally, allowing TDs on only 4 of their 17 defensive red zone trips. They must put something in the water in Blacksburg, cause that's ridiculous.

Oklahoma and Florida are #2 and 5, respectively. It's just not fair to put defenses that tough opposite offenses with the kind of firepower they have (assuming their QBs are healthy, anyway.)

Thoughts? I just ran these numbers for fun, but is this something I should revisit every couple weeks?

EDIT - I added in the "PPT" column. This is the "points per red zone trip" metric discussed in the comments, and it's what I used for my red zone offense post here. This didn't change the rankings too much - if I reranked based on the new metric, Wisconsin would leapfrog Northwestern and Illinois by a slim margin, but that's it. Also of interest is that using the PPT metric, OSU gets jumped by Arizona and Louisiana-Monroe, leaving the Bucks dead last in NCAA D1A. That makes me smile inside, even if it is just an artifact of a small sample size.